• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.4
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• pp.347-354
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• 2007

Since large portal service providers started web services for 3D city models around the world using spatial imagery, the competition has been getting intense to provide the models with the higher quality and accuracy. The building models are the most in number among the 3D city model objects, and it takes much time and money to create realistic model due to various shapes and visual appearances of building object. The aforementioned problem is the most significant limitation for the service and the update of the 3D city model of the large area. This study proposed a method of generating realistic 3D building models with quick and economical texture mapping using multiple spatial imagery such as aerial photos or satellite images after reconstructed geometric models of buildings from building layers in digital maps. Based on the experimental results, the suggested method has effectiveness for the generation of the 3D building models using various air-borne imagery and satellite imagery quickly and economically.

• Journal of the Korean Geotechnical Society
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• v.25 no.9
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• pp.93-100
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• 2009

A core procedure of the direct search method used in this study is optimizing a difference between objective function and real displacement and correcting unknown variables. Because the research procedure comes from back-analyzing of the unknown variable of each layer, back-analyzing results need an additional optimization to minimize interferential effects of unknown variables. Therefore, the direct search method Is used to obtain optimized solutions without a partial differentiation of an objective function. The object of this research is developing the back analysis technique for multi-unknown variables by modeling the soil including underground structure Into upper and lower layer. In order to minimize interferent errors, repeated back analysis is performed and applicability on the real tunnel is examined. Consequently, the multi-layer analysis model is more precise in describing the real behavior of underground structure. It shows the validity of back analysis far multi-layer model which is the understructure placed on multi-layer boundaries.

• Journal of Advanced Navigation Technology
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• v.27 no.5
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• pp.495-501
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• 2023

P-3C/K aircraft for maritime patrols that Republic of Korea Navy is using, is equipped with a variety of sensors and communication devices. Collected data from the aircraft is managed as tactical information by flight operators and stored. When the flight mission is completed, this information is transferred to tactical support center on the ground and played back or used for follow-up work through a analysis tool. During a flight mission, there are tens of thousands of detection objects within an hour in KADIZ (Korea air defense identification zone). In contrast, in TSD (tactical situation display), which displays a map when using the analysis tool, all detected objects are expressed as symbols. The increase in display symbols has a significant impact on the TSD image updating and consequently interferes with the smooth operation of operators. In this paper, we propose applying multiple threads and multiple layers to improve the performance of existing TSD. And the performance improvement is proven through the execution results.

• International Journal of Heart Failure
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• v.6 no.1
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• pp.11-19
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• 2024

The prevalence of heart failure (HF) is increasing, necessitating accurate diagnosis and tailored treatment. The accumulation of clinical information from patients with HF generates big data, which poses challenges for traditional analytical methods. To address this, big data approaches and artificial intelligence (AI) have been developed that can effectively predict future observations and outcomes, enabling precise diagnoses and personalized treatments of patients with HF. Machine learning (ML) is a subfield of AI that allows computers to analyze data, find patterns, and make predictions without explicit instructions. ML can be supervised, unsupervised, or semi-supervised. Deep learning is a branch of ML that uses artificial neural networks with multiple layers to find complex patterns. These AI technologies have shown significant potential in various aspects of HF research, including diagnosis, outcome prediction, classification of HF phenotypes, and optimization of treatment strategies. In addition, integrating multiple data sources, such as electrocardiography, electronic health records, and imaging data, can enhance the diagnostic accuracy of AI algorithms. Currently, wearable devices and remote monitoring aided by AI enable the earlier detection of HF and improved patient care. This review focuses on the rationale behind utilizing AI in HF and explores its various applications.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.6
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• pp.15-26
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• 2012

In this paper, we perform interference cancellation in multiuser MIMO (Multiple Input Multiple Output) relay network with improved Amplify-and-Forward (AF) and Decode-and-Forward (DF) relay protocols. The work of interference cancellation is followed by evolved NodeB (eNB), Relay Node (RN) and User Equipment (UE) to improve the error performance of whole transmission system with the explicit use of relay node. In order to perform interference cancellation, we use Dirty Paper Coding (DPC) and Thomilson Harashima Precoding (THP) allied with detection techniques Zero Forcing (ZF), Minimum Mean Square Error (MMSE), Successive Interference Cancellation (SIC) and Ordered Successive Interference Cancellation (OSIC). These basic techniques are studied and improved in the proposal by using the functions of relay node. The performance is improved by Decode-and-Forward which enhance the cancellation of interference in two layers at the cooperative relay node. The interference cancellation using weighted vectors is performed between eNB and RN. In the final results of the research, we conclude that in contrast with the conventional algorithms, the proposed algorithm shows better performance in lower SNR regime. The simulation results show the considerable improvement in the bit error performance by the proposed scheme in the LTE-Advanced system.

• Spatial Information Research
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• v.7 no.2
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• pp.159-173
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• 1999

GIS has been regarded as one of important tools or methodologies for various geoscience applications. Recently, spatial data integration schemes for site-specific or field-specific thematic mapping are newly developed and utilized. However, these kinds of approaches are somewhat insufficient quantitative assessment of integrated layers towards known targets in-detailed . Moreover, GIS analysis scheme is rarely extended to scientific approaches. In this study, simple approach of Multi-Buffer Zone Analysis , related to GIS analystical aspect, is addressed and an actual application for predicting or favorable mapping of mineral occurrences, one of GIS-based geoscientific approaches, is performed, As for geo-processing in GIS itself, this scheme can be regarded as extension or adaptiation of cell-based buffering or proximity analysis to geoscientific data interpretation. This study is based on rationale that surface geological pattern around primitives such as a point, a line, or a polygon in GIS, representing significant geological features, can be efficiently utilized to delineate complex geological behaviors or events, especially handling multiple dta sets originated from multiple sources such as airborne geophysical/radiometric exploration, field survey, and even a classified image of remote sensing. Conclusively, this methodology associated wit GIS is though to be helpful to analyze the spatial pattern of multiple data, pointing given sources, and is expected to effectively utilize for exploratory analysis of cell-based resultant layer integrated with complex or different data sources.

• Journal of the Korean Vacuum Society
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• v.20 no.6
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• pp.449-455
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• 2011

The luminescence properties of $In_{0.5}Ga_{0.5}As/In_{0.5}Al_{0.5}As$ multiple quantum wells (MQWs) grown on $In_{0.4}Al_{0.6}As$ buffer layer have been investigated by using photoluminescence (PL) and time-resolved PL measurements. A 1-${\mu}m$-thick $In_{0.4}Al_{0.6}As$ buffer layers were deposited at various temperatures from $320^{\circ}C$ to $580^{\circ}C$ on a 500-nm-thick GaAs layer, and then 1-${\mu}m$-thick $In_{0.5}Al_{0.5}As$ layers were deposited at $480^{\circ}C$, followed by the deposition of the InGaAs/InAlAs MQWs. In order to study the effects of $In_{0.4}Al_{0.6}As$ layer on the optical properties of the MQWs, four different temperature sequences are used for the growth of $In_{0.4}Al_{0.6}As$ buffer layer. The MQWs consist of three $In_{0.5}Al_{0.5}As$ wells with different well thicknesses (2.5-nm, 4.0-nm, and 6.0-nm-thick) and 10-nm-thick $In_{0.5}Al_{0.5}As$ barriers. The PL peaks from 4-nm QW and 6-nm QW were observed. However, for the MQWs on the $In_{0.4}Al_{0.6}As$ layer grown by using the largest growth temperature variation (320-$580^{\circ}C$), the PL spectrum only showed a PL peak from 6-nm QW. The carrier decay times in the 4-nm QW and 6-nm QW were measured from the emission wavelength dependence of PL decay. These results indicated that the growth temperatures of $In_{0.4}Al_{0.6}As$ layer affect the optical properties of the MQWs.

• Transactions on Electrical and Electronic Materials
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• v.10 no.2
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• pp.35-39
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• 2009

A novel Helmholtz coil inductively coupled plasma(H-ICP) etcher is proposed and characterized for deep nano-scale CMOS technology. Various hardware tests are performed while varying key parameters such as distance between the top and bottom coils, the distance between the chamber ceiling and the wafer, and the chamber height in order to determine the optimal design of the chamber and optimal process conditions. The uniformity was significantly improved by applying the optimum conditions. The plasma density obtained with the H-ICP source was about $5{\times}10^{11}/cm^3$, and the electron temperature was about 2-3 eV. The etching selectivity for the poly-silicon gate versus the ultra-thin gate oxide was 482:1 at 10 sccm of $HeO_2$. The proposed H-ICP was successfully applied to form multiple 60-nm poly-silicon gate layers.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.1
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• pp.581-584
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• 2014

Skin is the soft outer covering of vertebrates. In mammals, the skin is the largest organ of the integumentary system made up of multiple layers of ectodermal tissue, and guards the underlying muscles, bones, ligaments and internal organs. There is a difference of the physiological function and anatomical structure of the skin, as body parts, sex, age, race and nutritional status. In this study, we measured the moisturizing ability of the skin of the 20s Chinese and Korea in Korean. We found that the skin hydrating of Chinese is significantly higher than Korean and TEWL of Chinese is lower than Korean. We measured the moisturizing ability of both 20s Chinese and Korean. As result, the moisturizing ability of 20s Chinese is better than Korean.

• Women's Health Nursing
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• v.26 no.1
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• pp.5-9
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• 2020

Artificial intelligence (AI), which includes machine learning and deep learning has been introduced to nursing care in recent years. The present study reviews the following topics: the concepts of AI, machine learning, and deep learning; examples of AI-based nursing research; the necessity of education on AI in nursing schools; and the areas of nursing care where AI is useful. AI refers to an intelligent system consisting not of a human, but a machine. Machine learning refers to computers' ability to learn without being explicitly programmed. Deep learning is a subset of machine learning that uses artificial neural networks consisting of multiple hidden layers. It is suggested that the educational curriculum should include big data, the concept of AI, algorithms and models of machine learning, the model of deep learning, and coding practice. The standard curriculum should be organized by the nursing society. An example of an area of nursing care where AI is useful is prenatal nursing interventions based on pregnant women's nursing records and AI-based prediction of the risk of delivery according to pregnant women's age. Nurses should be able to cope with the rapidly developing environment of nursing care influenced by AI and should understand how to apply AI in their field. It is time for Korean nurses to take steps to become familiar with AI in their research, education, and practice.